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junzis
GitHub Repository: junzis/openap
 Path: blob/master/scripts/wrap_csv_to_fwf.py
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import os

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import glob

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import yaml

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import numpy as np

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import pandas as pd

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from tabulate import tabulate

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def to_fwf(df, fname):

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    content = tabulate(df.values.tolist(), list(df.columns), tablefmt="plain", numalign="left", stralign="left")

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    open(fname, "w").write(content)

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pd.DataFrame.to_fwf = to_fwf

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root = os.path.dirname(os.path.realpath(__file__))

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phases = {

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    'TO': 'takeoff',

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    'IC': 'initial_climb',

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    'CL': 'climb',

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    'CR': 'cruise',

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    'DE': 'descent',

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    'FA': 'final_approach',

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    'LD': 'landing',

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}

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prop = {

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    'to_v_lof':               'Liftoff speed'                               ,

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    'to_d_tof':               'Takeoff distance'                            ,

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    'to_acc_tof':             'Mean takeoff accelaration'                   ,

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    'ic_va_avg':              'Mean airspeed'                               ,

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    'ic_vs_avg':              'Mean vertical rate'                          ,

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    'ic_va_std':              'Standard deviation of airspeed'              ,

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    'ic_vs_std':              'Standard deviation of vertical rate '        ,

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    'cl_d_range':             'Climb range'                                 ,

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    'cl_v_cas_const':         'Constant CAS'                                ,

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    'cl_v_mach_const':        'Constant Mach'                               ,

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    'cl_h_cas_const':         'Constant CAS crossover altitude'             ,

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    'cl_h_mach_const':        'Constant Mach crossover altitude'            ,

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    'cl_vs_avg_pre_cas':      'Mean climb rate, pre-constant-CAS'           ,

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    'cl_vs_avg_cas_const':    'Mean climb rate, constant-CAS'               ,

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    'cl_vs_avg_mach_const':   'Mean climb rate, constant-Mach'              ,

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    'cr_d_range':             'Cruise range'                                ,

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    'cr_v_cas_mean':          'Mean cruise CAS'                             ,

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    'cr_v_cas_max':           'Maximum cruise CAS'                          ,

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    'cr_v_mach_mean':         'Mean cruise Mach'                            ,

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    'cr_v_mach_max':          'Maximum cruise Mach'                         ,

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    'cr_h_init':              'Initial cruise altitude'                     ,

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    'cr_h_mean':              'Mean cruise altitude'                        ,

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    'cr_h_max':               'Maximum cruise altitude'                     ,

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    'de_d_range':             'Descent range'                               ,

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    'de_v_mach_const':        'Constant Mach'                               ,

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    'de_v_cas_const':         'Constant CAS'                                ,

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    'de_h_cas_const':         'Constant CAS crossover altitude'             ,

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    'de_h_mach_const':        'Constant Mach crossover altitude'            ,

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    'de_vs_avg_cas_const':    'Mean descent rate, constant-CAS'             ,

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    'de_vs_avg_mach_const':   'Mean descent rate, constant-Mach'            ,

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    'de_vs_avg_after_cas':    'Mean descent rate, after-constant-CAS'       ,

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    'fa_va_avg':              'Mean airspeed'                               ,

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    'fa_vs_avg':              'Mean vertical rate'                          ,

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    'fa_va_std':              'Standard deviation of airspeed'              ,

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    'fa_vs_std':              'Standard deviation of vertical rate'         ,

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    'fa_agl':                 'Approach angle'                              ,

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    'ld_v_app':               'Touchdown speed'                             ,

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    'ld_d_brk':               'Braking distance'                            ,

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    'ld_acc_brk':             'Mean braking acceleration'                   ,

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}

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files = sorted(glob.glob('input/wrap/*.csv'))

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for f in files:

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    mdl = f[-8:-4]

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    print(mdl)

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    df = pd.read_csv(f)

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    for i, r in df.iterrows():

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        df.loc[i, 'phase'] = phases[r.phase]

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        df.loc[i, 'note'] = prop[r.param]

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    df = df[['param', 'phase', 'note', 'opt', 'min', 'max', 'model', 'pm']]

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    df.columns = ['variable', 'flight phase', 'name', 'opt', 'min', 'max', 'model', 'parameters']

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    df.to_fwf(root+'/../openap/data/wrap/%s.txt' % mdl)

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